Human fatigue models tend to be probabilistic in nature and require several parameters in order to create realistic results. Uncertainties often must be associated with each of these parameters and with the model system as a whole. Prediction tasks therefore tend to be rather demanding computationally. Unfortunately, not all fatigue-calculation scenarios lend themselves to the presence of a computing device capable of intensive computation. Certain work and testing environments require mobility, have a shortage of physical space for computing equipment, or otherwise make access to powerful computing equipment unfeasible. There is a general desire to provide tools for assessing and/or otherwise predicting the alertness of individuals.